16,120 research outputs found
Autonomous Tissue Scanning under Free-Form Motion for Intraoperative Tissue Characterisation
In Minimally Invasive Surgery (MIS), tissue scanning with imaging probes is
required for subsurface visualisation to characterise the state of the tissue.
However, scanning of large tissue surfaces in the presence of deformation is a
challenging task for the surgeon. Recently, robot-assisted local tissue
scanning has been investigated for motion stabilisation of imaging probes to
facilitate the capturing of good quality images and reduce the surgeon's
cognitive load. Nonetheless, these approaches require the tissue surface to be
static or deform with periodic motion. To eliminate these assumptions, we
propose a visual servoing framework for autonomous tissue scanning, able to
deal with free-form tissue deformation. The 3D structure of the surgical scene
is recovered and a feature-based method is proposed to estimate the motion of
the tissue in real-time. A desired scanning trajectory is manually defined on a
reference frame and continuously updated using projective geometry to follow
the tissue motion and control the movement of the robotic arm. The advantage of
the proposed method is that it does not require the learning of the tissue
motion prior to scanning and can deal with free-form deformation. We deployed
this framework on the da Vinci surgical robot using the da Vinci Research Kit
(dVRK) for Ultrasound tissue scanning. Since the framework does not rely on
information from the Ultrasound data, it can be easily extended to other
probe-based imaging modalities.Comment: 7 pages, 5 figures, ICRA 202
Assistance strategies for robotized laparoscopy
Robotizing laparoscopic surgery not only allows achieving better
accuracy to operate when a scale factor is applied between master and slave or thanks to the use of tools with 3 DoF, which cannot be used in conventional manual surgery, but also due to additional informatic support. Relying on computer assistance different strategies that facilitate the task of the surgeon can be incorporated, either in the form of autonomous navigation or cooperative guidance, providing sensory or visual feedback, or introducing certain limitations of movements. This paper describes different ways of assistance aimed at improving the work capacity of the surgeon and achieving more safety for the patient, and the results obtained with the prototype developed at UPC.Peer ReviewedPostprint (author's final draft
kPAM 2.0: Feedback Control for Category-Level Robotic Manipulation
In this paper, we explore generalizable, perception-to-action robotic
manipulation for precise, contact-rich tasks. In particular, we contribute a
framework for closed-loop robotic manipulation that automatically handles a
category of objects, despite potentially unseen object instances and
significant intra-category variations in shape, size and appearance. Previous
approaches typically build a feedback loop on top of a real-time 6-DOF pose
estimator. However, representing an object with a parameterized transformation
from a fixed geometric template does not capture large intra-category shape
variation. Hence we adopt the keypoint-based object representation proposed in
kPAM for category-level pick-and-place, and extend it to closed-loop
manipulation policies with contact-rich tasks. We first augment keypoints with
local orientation information. Using the oriented keypoints, we propose a novel
object-centric action representation in terms of regulating the linear/angular
velocity or force/torque of these oriented keypoints. This formulation is
surprisingly versatile -- we demonstrate that it can accomplish contact-rich
manipulation tasks that require precision and dexterity for a category of
objects with different shapes, sizes and appearances, such as peg-hole
insertion for pegs and holes with significant shape variation and tight
clearance. With the proposed object and action representation, our framework is
also agnostic to the robot grasp pose and initial object configuration, making
it flexible for integration and deployment.Comment: IEEE Robotics and Automation Letter. The video demo is on
https://sites.google.com/view/kpam2
Image-Guided Robot-Assisted Techniques with Applications in Minimally Invasive Therapy and Cell Biology
There are several situations where tasks can be performed better robotically rather than manually. Among these are situations (a) where high accuracy and robustness are required, (b) where difficult or hazardous working conditions exist, and (c) where very large or very small motions or forces are involved. Recent advances in technology have resulted in smaller size robots with higher accuracy and reliability. As a result, robotics is fi nding more and more applications in Biomedical Engineering. Medical Robotics and Cell Micro-Manipulation are two of these applications involving interaction with delicate living organs at very di fferent scales.Availability of a wide range of imaging modalities from ultrasound and X-ray fluoroscopy to high magni cation optical microscopes, makes it possible to use imaging as a powerful means to guide and control robot manipulators. This thesis includes three parts focusing on three applications of Image-Guided Robotics in biomedical engineering, including: Vascular Catheterization: a robotic system was developed to insert a
catheter through the vasculature and guide it to a desired point via visual servoing. The system provides shared control with the operator to perform a task semi-automatically or through master-slave control. The system provides control of a catheter tip with high accuracy while reducing X-ray exposure to the clinicians and providing a more ergonomic situation for the cardiologists. Cardiac Catheterization: a master-slave robotic system was developed
to perform accurate control of a steerable catheter to touch and ablate faulty regions on the inner walls of a beating heart in order to treat arrhythmia. The system facilitates touching and making contact with a target point in a beating heart chamber through master-slave control with coordinated visual feedback. Live Neuron Micro-Manipulation: a microscope image-guided robotic
system was developed to provide shared control over multiple micro-manipulators to touch cell membranes in order to perform patch clamp electrophysiology.
Image-guided robot-assisted techniques with master-slave control were implemented for each case to provide shared control between a human operator and a robot. The results show increased accuracy and reduced operation time in all three cases
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